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ZENODO
Dataset . 2018
License: CC BY SA
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2018
License: CC BY SA
Data sources: Datacite
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3D Dataset "Computation Of Exact G-Factor Maps In 3D Grappa Reconstructions"

Authors: Rabanillo, Iñaki; Zhu, Ante; Aja-Fernández, Santiago; Alberola-López, Carlos; Hernando, Diego;

3D Dataset "Computation Of Exact G-Factor Maps In 3D Grappa Reconstructions"

Abstract

Datasets used in the paper entitled "", containing the following acquisitions: 1) Simulated abdomen data set: we have synthetized a 3D volume using the simulation environment XCAT based on the extended cardio-torso phantom. We simulated a T1-weighted acquisition using the following acquisition parameters: TE/TR=1.5/3ms, flip angle=60º, acquisition matrix size=60x60x32. A 32-coil acquisition was simulated by modulating the image using artificial sensitivity maps coded for each coil. The noise-free coil images were transformed into the \bk--space and corrupted with synthetic Gaussian noise characterized by the matrices \(\Gamma_k\)and \(C_k\) with SNR=25 for each coil, and the correlation coefficient between coils was set to \(\rho\)=0.1$. For statistical purposes, 4000 realizations of each image were used. 2) Water phantom acquisition: A MR phantom sphere with solution (GE Medical Systems, Milwaukee, WI) was scanned in a 32-channel head coil on a 3.0T scanner (MR750, GE Healthcare, Waukesha, WI). A spoiled gradient-echo acquisition with 100 realizations of the same fully-encoded k-space sampling was used. Acquisition parameters included: coronal view, TE/TR=0.96/3.69ms, flip angle=12º, field of view=22x22$x30.7\(cm³\), acquisition matrix size=60x60x32, bandwidth=62.5KHz. We corrected for \(B_0\) field drift related phase variations and magnitude decay by a pre-processing step. First we estimated the phase-shift between realizations from the center of the k-space as a cubic function of time and removed it afterwards. And, second, we estimated the magnitude-decay in the k-space as a linear function and substracted it in order not to affect the noise. 3) In vivo acquisition: in order to assess the feasibility of the proposed method, after obtaining the approval fo the local institutional review board (IRB), a volunteer was scanned in a 32-channel head coil on a 3.0T scanner (MR750, GE Healthcare, Waukesha, WI). A spoiled gradient-echo acquisition of a fully-encoded \bk--space sampling was used. Acquisition parameters included: coronal view, TE/TR=2.2/5.7ms, flip angle=12º,field of view=22x22x22\(cm³\), matrix size=220x220x220, bandwidth=62.5$KHz.

The authors acknowledge MICIN for grants TEC2013-44194P, TEC 2014-57428 and TEC2017-82408-R, as well as Junta de Castilla y León for grant VA069U16. The first author acknowledges MINECO for FPI grant BES-2014-069524.

Keywords

Phantom, GRAPPA, Parallel Imaging, Noise, MRI

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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